基于RBF神经网络的混沌背景下瞬态弱信号检测

Transient Signal in Chaos Detection Based on RBF Neural Network

针对海杂波背景下瞬态弱信号检测的问题,采用海杂波混沌模型,基于神经网络重构混沌序列相空间,提出了基于RBF神经网络预测混沌时间序列和瞬态弱信号检测方案。理论分析和仿真结果表明这种方法能够有效实现混沌背景噪声中瞬态弱信号的检测。

The detection of weak signal submerged in chaos is discussed in this paper. In classical statistic detection theory the chaotic noise is regarded as a random signal, which will greatly reduce the performance of signal detection. To improve the performance based on chaotic dynamic mechanism, by using neural network to establish forecast model of chaotic time series and restructure its phase space, and based on the neural network＇s powerful ability of studying and nonlinear processing and local predictability of chaos, the method of neural network prediction and detection weak signal in chaotic time series is proposed, the results of theoretical analysis and simulation indicate that the method is effective.